Embedded Voice for AI Assistants
Add voice to an existing AI assistant product. Guava handles the call; your backend handles reasoning. One callback, your model in the loop.
Why this matters
Embed Guava in your AI stack. Your prompts, your data, our voice infrastructure. Sub-1s latency. WebRTC + SIP. Compliance you can hand to your enterprise buyer. This example shows you how to automate embedded voice for ai assistants calls end-to-end with Guava's SDK — no telephony plumbing, no prompt engineering, just Python.
Installation
Install from Guava's private PyPI index. A public package is coming soon — the install command will simplify to pip install guava.
# Step 1: Install Guava
pip install gridspace-guava --extra-index-url https://guava-pypi.gridspace.com
# Public PyPI package coming soon — the install command will simplify to:
# pip install guava
# Step 2: Set your credentials
export GUAVA_API_KEY="..."
export GUAVA_AGENT_NUMBER="..."How it's built
Every Guava agent is a Python class. Walk through the key sections below, then grab the complete file at the end.
Imports
Import the Guava SDK and any helpers you need. guava.CallController is the base class for every voice agent.
# Install: pip install gridspace-guava --extra-index-url https://guava-pypi.gridspace.com
import guava
import os
import requestsAgent setup
set_persona() defines how the agent presents itself. set_task() gives it its mission in plain English. The checklist drives the conversation — Guava works through it top-to-bottom, collecting Field values and speaking Say items as it goes.
class EmbeddedAssistantBot(guava.CallController):
def __init__(self, assistant_id: str, user_id: str):
super().__init__()
self.assistant_id = assistant_id
self.user_id = user_id
self.thread_id = None
self.set_persona(
organization_name="Acme AI",
agent_name="Atlas",
)
self.set_task(
objective="Carry on an open-ended conversation, deferring reasoning to the customer's AI backend.",
checklist=[
"Greet the caller and ask how you can help today.",
guava.OpenEnded(
description="Take any user utterance and call route_to_backend() to get the assistant's reply.",
handler=self.route_to_backend,
),
],
)
def route_to_backend(self, utterance: str) -> str:
"""Forward the user's words to the customer's AI backend and return its reply."""
response = requests.post(
"https://api.acme-ai.example/v1/threads/messages",
json={
"assistant_id": self.assistant_id,
"user_id": self.user_id,
"thread_id": self.thread_id,
"message": utterance,
},
headers={"Authorization": f"Bearer {os.environ['ACME_API_KEY']}"},
timeout=8,
).json()
self.thread_id = response.get("thread_id")
return response["reply"]
guava.listen(
controller=EmbeddedAssistantBot,
controller_args={"assistant_id": "asst_general", "user_id": "u_test_001"},
agent_number=os.environ["GUAVA_AGENT_NUMBER"],
api_key=os.environ["GUAVA_API_KEY"],
)Platform performance
<1s
Response time
99.99%
Uptime SLA
13+
Industries served
Full example
The complete file — copy it, save it as example.py, and run it.
# Install: pip install gridspace-guava --extra-index-url https://guava-pypi.gridspace.com
import guava
import os
import requests
class EmbeddedAssistantBot(guava.CallController):
def __init__(self, assistant_id: str, user_id: str):
super().__init__()
self.assistant_id = assistant_id
self.user_id = user_id
self.thread_id = None
self.set_persona(
organization_name="Acme AI",
agent_name="Atlas",
)
self.set_task(
objective="Carry on an open-ended conversation, deferring reasoning to the customer's AI backend.",
checklist=[
"Greet the caller and ask how you can help today.",
guava.OpenEnded(
description="Take any user utterance and call route_to_backend() to get the assistant's reply.",
handler=self.route_to_backend,
),
],
)
def route_to_backend(self, utterance: str) -> str:
"""Forward the user's words to the customer's AI backend and return its reply."""
response = requests.post(
"https://api.acme-ai.example/v1/threads/messages",
json={
"assistant_id": self.assistant_id,
"user_id": self.user_id,
"thread_id": self.thread_id,
"message": utterance,
},
headers={"Authorization": f"Bearer {os.environ['ACME_API_KEY']}"},
timeout=8,
).json()
self.thread_id = response.get("thread_id")
return response["reply"]
guava.listen(
controller=EmbeddedAssistantBot,
controller_args={"assistant_id": "asst_general", "user_id": "u_test_001"},
agent_number=os.environ["GUAVA_AGENT_NUMBER"],
api_key=os.environ["GUAVA_API_KEY"],
)Run it
Start the agent. It will connect to Guava's infrastructure and begin accepting calls on your assigned number.
python example.py